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   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "历年本专科毕业生之和： 8821.5568\n",
      "高等教育人口比例约：8.33%\n",
      "2000年后本专科毕业生之和： 7330.7347 0.8310023804415112\n"
     ]
    }
   ],
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    "def get_list(data):\n",
    "    list_data = data.split('\t')\n",
    "    list_data.reverse()\n",
    "    list_data = [float(i or 0) for i in list_data]\n",
    "    return list_data\n",
    "\n",
    "data_bk = '704.1800\t680.8866\t659.3671\t638.7210\t624.7000\t608.1600\t575.4200\t531.1000\t511.9500\t447.7900\t377.5000\t306.8000\t239.1000\t187.7000\t133.7300\t103.6300\t94.9800\t84.7600\t82.9833\t82.9070\t83.8638\t80.5000\t63.7417\t57.0715\t60.4223\t61.4267\t61.4000\t57.6242\t55.3466\t53.1900\t39.2800\t31.6000\t28.6937\t33.5344\t45.7244\t13.9640\t14.7000\t8.5085\t16.5000\t19.4000\t14.9000\t11.9000\t4.3000\t3.0000\t1.7000\t0.6000\t10.3000\t15.0000\t15.0000\t12.5000\t14.1000\t18.6000\t20.4000\t19.9000\t17.7000\t15.1000\t13.6000\t7.0000\t7.2000\t5.6000\t6.3000\t5.5000\t4.7000\t4.8000\t3.2000\t1.9000\t1.8000\t2.1000'\n",
    "list_bk = get_list(data_bk)\n",
    "all_bk = sum(list_bk)\n",
    "print('历年本专科毕业生之和：', all_bk)\n",
    "\n",
    "print('高等教育人口比例约：%.2f%%' % ((all_bk + 2695.8433) / 138271 * 100))\n",
    "\n",
    "all_bk_near = sum(list_bk[-16:])\n",
    "print('2000年后本专科毕业生之和：', all_bk_near, all_bk_near / all_bk)"
   ]
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  {
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   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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    "data_yjs = '56.3938\t55.1522\t53.5863\t51.3626\t48.6455\t42.9994\t38.3600\t37.1273\t34.4825\t31.1839\t25.5902\t18.9728\t15.0777\t11.1091\t8.0841\t6.7809\t5.8767\t5.4670\t4.7077\t4.6539\t3.9652\t3.1877\t2.8047\t2.8214\t2.5692\t3.2537\t3.5440\t3.7232\t4.0838\t2.7603\t1.6950\t1.7004\t0.2756\t0.4497\t0.4058\t1.1669\t0.0476\t0.0140\t0.0009\t\t\t\t\t\t\t\t\t0.1317\t0.1240\t0.0852\t0.1137\t0.1665\t0.0895\t0.1512\t0.1019\t0.0179\t0.0589\t0.0727\t0.1113\t0.1723\t0.2349\t0.1730\t0.0660\t0.1177\t0.0627\t0.0166\t0.0159\t0.0107'\n",
    "list_yjs = get_list(data_yjs)\n",
    "\n",
    "data_lxs ='43.2500\t40.9100\t36.4800\t35.3500\t27.2900\t18.6200\t13.4800\t10.8300\t6.9300\t4.4000\t4.2000\t3.4987\t2.4726\t2.0152\t1.7945\t1.2243\t0.9121\t0.7748\t0.7379\t0.7130\t0.6570\t0.5750\t0.4230\t0.5128\t0.3611\t0.2069\t0.1593\t0.1756\t0.3000\t0.1605\t0.1388\t0.1424\t0.2290\t0.2303\t0.2116\t0.1143\t0.0162\t0.0231\t0.0248\t0.0270\t0.0189\t0.0186\t0.0070\t\t\t\t\t\t\t\t\t0.0199\t0.0191\t0.0426\t0.0980\t0.1403\t0.2217\t0.1380\t0.0670\t0.0347\t0.0258\t0.0104\t0.0022\t0.0016\t\t\t\t'\n",
    "list_lxs = get_list(data_lxs)\n",
    "\n",
    "list_edu = []\n",
    "for i in zip(list_bk, list_yjs, list_lxs):\n",
    "    list_edu.append(int(sum(i) * 10000))\n",
    "print(list_edu)\n",
    "\n",
    "data_total = '138271\t137462\t136782\t136072\t135404\t134735\t134091\t133450\t132802\t132129\t131448\t130756\t129988\t129227\t128453\t127627\t126743\t125786\t124761\t123626\t122389\t121121\t119850\t118517\t117171\t115823\t114333\t112704\t111026\t109300\t107507\t105851\t104357\t103008\t101654\t100072\t98705\t97542\t96259\t94974\t93717\t92420\t90859\t89211\t87177\t85229\t82992\t80671\t78534\t76368\t74542\t72538\t70499\t69172\t67296\t65859\t66207\t67207\t65994\t64653\t62828\t61465\t60266\t58796\t57482\t56300\t55196\t54167'\n",
    "list_total = get_list(data_total)\n",
    "\n",
    "rate_edu = []\n",
    "for i in zip(list_edu, list_total):\n",
    "    rate_edu.append(i[0] / (i[1] * 10000) * 100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
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       "    \"title\": [\n",
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       "            \"top\": \"auto\",\n",
       "            \"subtextStyle\": {\n",
       "                \"fontSize\": 12\n",
       "            }\n",
       "        }\n",
       "    ]\n",
       "};\n",
       "myChart_0b85b826d8b844fdb0390ffbde5cb4a7.setOption(option_0b85b826d8b844fdb0390ffbde5cb4a7);\n",
       "\n",
       "    });\n",
       "</script>\n"
      ],
      "text/plain": [
       "<pyecharts.custom.overlap.Overlap at 0x10a9b4898>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from pyecharts import Bar, Line, Overlap\n",
    "\n",
    "years = [str(i) for i in range(1949, 2017)]\n",
    "bar = Bar(\"毕业生年度变化表\")\n",
    "bar.add(\"本专科毕业生\", years, list_bk, is_stack=True)\n",
    "bar.add(\"研究生毕业生\", years, list_yjs, is_stack=True)\n",
    "bar.add(\"归国留学生\", years, list_lxs, is_stack=True)\n",
    "bar\n",
    "line = Line()\n",
    "line.add(\"高等教育毕业生占人口比例\", years, rate_edu, line_width=3)\n",
    "ol = Overlap()\n",
    "ol.add(bar)\n",
    "ol.add(line, is_add_yaxis=True, yaxis_index=1)\n",
    "ol"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.0, 0.0035, 0.038, 0.0231, 0.0675, 0.1518, 0.2093, 0.2401, 0.0529, 0.0415, 0.0576, 0.0441, 0.0124, 0.0114, 0.0032, 0.065, 0.0454, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0036, 0.0259, 0.018, 0.0245, 0.0277, 0.022, 0.086, 0.1777, 0.2124, 0.2922, 0.2326, 0.2633, 0.3073, 0.4888, 0.4676, 0.4703, 0.3786, 0.3329, 0.295, 0.29, 0.654, 1.0742, 1.9071, 2.0381, 2.0905, 2.241, 1.7622, 2.3749, 3.8989, 8.3973, 12.5179, 11.7307, 11.4682, 11.8515, 13.4, 14.4, 17.98, 22.93, 28.47, 33.97, 39.96, 41.39, 45.98, 52.37, 54.45]\n",
      "[0.14579686327748204, 0.14335471604662126, 0.17178855481770056, 0.21560489004377323, 0.29521157659368014, 0.31343283582089554, 0.3055555555555556, 0.3854282536151279, 0.47230702136938507, 0.4734808570425009, 0.5481307035619665, 0.6829329329329329, 0.8540710316501571, 0.7933884297520661, 0.7811724269620011, 0.7943067033976124]\n"
     ]
    }
   ],
   "source": [
    "data_cg = '54.4500\t52.3700\t45.9800\t41.3900\t39.9600\t33.9700\t28.4700\t22.9300\t17.9800\t14.4000\t13.4000\t11.8515\t11.4682\t11.7307\t12.5179\t8.3973\t3.8989\t2.3749\t1.7622\t2.2410\t2.0905\t2.0381\t1.9071\t1.0742\t0.6540\t0.2900\t0.2950\t0.3329\t0.3786\t0.4703\t0.4676\t0.4888\t0.3073\t0.2633\t0.2326\t0.2922\t0.2124\t0.1777\t0.0860\t0.0220\t0.0277\t0.0245\t0.0180\t0.0259\t0.0036\t\t\t\t\t\t\t0.0454\t0.0650\t0.0032\t0.0114\t0.0124\t0.0441\t0.0576\t0.0415\t0.0529\t0.2401\t0.2093\t0.1518\t0.0675\t0.0231\t0.0380\t0.0035\t'\n",
    "list_cg = get_list(data_cg)\n",
    "print(list_cg)\n",
    "rate_back = []\n",
    "for i in zip(list_lxs[-16:], list_cg[-16:]):\n",
    "    rate_back.append(i[1] and i[0] / i[1])\n",
    "print(rate_back)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "metadata": {},
   "outputs": [
    {
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    "years_near = years[-16:]\n",
    "\n",
    "bar = Bar(\"留学及归国人数年度变化表\")\n",
    "bar.add(\"出国留学人数\", years_near, list_cg[-16:])\n",
    "bar.add(\"学成归国人数\", years_near, list_lxs[-16:], bar_category_gap=15)\n",
    "bar\n",
    "line = Line()\n",
    "line.add(\"归国比例\", years_near, rate_back, line_width=3)\n",
    "ol = Overlap()\n",
    "ol.add(bar)\n",
    "ol.add(line, is_add_yaxis=True, yaxis_index=1)\n",
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   "cell_type": "code",
   "execution_count": 24,
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       "};\n",
       "myChart_d61d3e149b9e4ba48e23a1ffa2e68477.setOption(option_d61d3e149b9e4ba48e23a1ffa2e68477);\n",
       "\n",
       "    });\n",
       "</script>\n"
      ],
      "text/plain": [
       "<pyecharts.custom.overlap.Overlap at 0x10a9c7e10>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_born_rate = '12.95\t12.07\t12.37\t12.08\t12.10\t11.93\t11.90\t11.95\t12.14\t12.10\t12.09\t12.40\t12.29\t12.41\t12.86\t13.38\t14.03\t14.64\t15.64\t16.57\t16.98\t17.12\t17.70\t18.09\t18.24\t19.68\t21.06\t21.58\t22.37\t23.33\t22.43\t21.04\t19.90\t20.19\t22.28\t20.91\t18.21\t17.82\t18.25\t19.03\t20.01\t23.13\t24.95\t28.07\t29.92\t30.74\t33.59\t34.25\t35.75\t34.12\t35.21\t38.00\t39.34\t43.60\t37.22\t18.13\t20.86\t24.78\t29.22\t34.03\t31.90\t32.60\t37.97\t37.00\t37.00\t37.80\t37.00\t36.00'\n",
    "list_born_rate = get_list(data_born_rate)\n",
    "list_born = []\n",
    "for i in zip(list_total, list_born_rate):\n",
    "    list_born.append(i[0] * i[1] / 1000)\n",
    "print(list_born)\n",
    "\n",
    "data_zs = '748.6110\t737.8495\t721.3987\t699.8330\t688.8300\t681.5000\t661.7600\t639.4900\t607.6600\t565.9200\t546.1000\t504.4600\t447.3000\t382.2000\t320.5000\t268.2800\t220.6100\t159.6800\t108.3627\t100.0393\t96.5812\t92.6000\t89.9846\t92.3952\t75.4192\t61.9874\t60.9000\t59.7113\t66.9700\t61.6800\t57.2000\t61.9000\t47.5171\t39.1000\t31.5000\t27.9000\t28.1000\t27.5000\t40.2000\t27.3000\t21.7000\t19.1000\t16.5000\t15.0000\t13.4000\t4.2000\t4.2000\t\t\t\t\t16.4000\t14.7000\t13.3000\t10.7000\t16.9000\t32.3000\t27.4000\t26.5000\t10.6000\t18.5000\t9.8000\t9.2000\t8.1000\t7.9000\t5.2000\t5.8000\t3.1000'\n",
    "list_zs = get_list(data_zs)\n",
    "print(list_zs)\n",
    "\n",
    "rate_zs = []\n",
    "for i in zip(list_born[:-19], list_zs[19:]):\n",
    "    rate_zs.append(i[1] / i[0])\n",
    "print(rate_zs)\n",
    "\n",
    "years_19 = years[19:]\n",
    "\n",
    "bar = Bar(\"适龄大学入学比例\")\n",
    "bar.add(\"19岁人口数\", years_19, list_born[:-19])\n",
    "bar.add(\"本专科招生人数\", years_19, list_zs[19:])\n",
    "# bar\n",
    "line = Line()\n",
    "line.add(\"招生比例\", years_19, rate_zs, line_width=3)\n",
    "ol = Overlap()\n",
    "ol.add(bar)\n",
    "ol.add(line, is_add_yaxis=True, yaxis_index=1)\n",
    "ol"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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